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Research on person re-identification based on posture guidance and feature alignment

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Abstract

This paper proposes a person re-identification algorithm utilizing posture guidance and feature alignment to solve posture difference and misalignment of the retrieved pedestrian images. Our technique employs Openpose to locate 18 key points on the human body and integrates 18 heat maps of various human body key points into a global feature representation. Then, a hard attention mechanism based on the human body key points forces the network to focus on the pedestrian posture features to align the same body parts of pedestrian imagery. Our architecture solves the pedestrian image posture difference and misalignment problem and performs robust person re-identification. We challenge the developed method on the public Market1501 and DukeMTMC-reID datasets, employing the Rank-1 and mAP performance metrics, and obtain 94.6%/81.4% and 85.7%/72.7%, respectively. The results highlight that the proposed algorithm solves the problems of pedestrian image misalignment and posture difference, proving the effectiveness and practicability of the proposed algorithm.

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The datasets are open and available.

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Funding

This work was supported by National Natural Science Foundation of China (No. 61861037) and the Ningxia University Graduate Innovation Research Project (No.CXXM202223).

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Author notes

  1. Jin Che, Yuxia Zhang, Qi Yang and Yuting He have contributed equally to this work.

Authors and Affiliations

  1. School of Physics and Electronic-Electrical Engineering, Ningxia University, Wen Cui Street, Yinchuan, 750021, Ningxia, China

    Jin Che, Yuxia Zhang, Qi Yang & Yuting He

  2. Ningxia Key Laboratory of Intelligent Sensing for Desert Information, Ningxia University, Helan Mountain West Road Street, Yinchuan, 750021, Ningxia, China

    Jin Che, Yuxia Zhang, Qi Yang & Yuting He

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  1. Jin Che
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  2. Yuxia Zhang
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  3. Qi Yang
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Contributions

JC: theoretical analysis, experimental methods, experimental ideas, review, and modify the first draft; YZ: preliminary experiment, experimental design, and draft writing; QY: further improved the experiment, conducted data analysis, and wrote the first draft; YH: data collation, draft writing, and editing.

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Correspondence to Jin Che.

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Communicated by I.Bartolini.

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Che, J., Zhang, Y., Yang, Q. et al. Research on person re-identification based on posture guidance and feature alignment. Multimedia Systems 29, 763–770 (2023). https://doi.org/10.1007/s00530-022-01016-3

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